In an era where data is the new oil, enterprises need to understand the core difference between being data-driven and data-aware Amplitude’s Chief Digital & Information Officer (CDIO) Chetna Mahajan told Silverlinings. The key difference? Silos.
Amplitude is a data analytics company that helps organizations track and analyze user data for insights around engagement, retention and revenue. With ever-growing amounts of data, and recent steps pushing generative AI (GenAI) forward, analysts and business leaders are seeing a need for improved management of that data — from architecture to governance — to support next-generation technologies.
Mahajan explained that a data-driven enterprise is empowered by a real-time data from across business units which is unified in a single cloud and made available to employees via a democratized system.
“Typically, you will have silos, and people will be looking at data in a particular set of systems that serve that business unit — HR will only look at Workday, or finance will look at NetSuite or Anaplan, sales will look at Salesforce — there is no centralized view of a holistic, end-to-end, 360 view of the customer,” Mahajan explained.
That means missed opportunities and a lag in decision making. Using the example of a contract renewal where fewer seats are being purchased, she noted that in a siloed world relevant data isn’t “coming into a [customer success manager’s] CSM’s world or to customer success team’s as a hot account because the churn signals are configured differently…Those two systems are not talking to each other.”
Mahajan believes this can be counteracted with a federated model where the central goal is to empower decision-makers with data in each sector of the enterprise. For example, Amplitude is aligned by business units, which she says allows decisions to be made based on information rather than “making a decision based on experience and intuition, which is a lot of times what a data-aware company would do.”
Building better data
To build the platform necessary to become a data-driven enterprise, Mahajan said enterprises should focus on what data is required for each use case rather than looking to build a giant cloud data warehouse.
“Let’s say churn is the biggest problem [in a business], I would pull in all the data that is required to build a 360 view of the whole churn analysis and then [look] to deliver that — whether it's to product data, specifically for sharing, such as product adoption,” or to financial data, she explained.
Eventually, yes — companies should aim to have a warehouse containing all the data, but it should be constructed by combining data that has been used to solve specific use cases “one step at a time.”
Entering the data race to be “best in class” rather than geared towards specific value ends up leaving companies “too slow to be able to respond to business needs,” Mahajan argued.
“It's not a flip of a switch. I think every company goes through a journey from being data-aware to data-driven, and you need to take it one step at a time. It's a cultural change. It's a huge change,” she concluded. “So, keep asking the question: Is data at the table?”